Approximate Semantic Tree Matching in OpenKnowledge

Abstract

The OpenKnowledge (OK) project is predicated on the idea that the peers involved in the peer-to-peer network do not have to have prior agreement on the representation and vocabulary they use or conform to pre-established standards. Instead, peers are permitted to represent their knowledge in any way they choose and the interaction between these disparate peers is controlled via interaction models(IMs), which describe how specific interactions proceed. These IMs describe the order of the message passing, the messages to be passed and the constraints on those messages for every peer in the interaction and are written in LCC; see Figure 2 for an example. Naturally, since representation and vocabulary are not fixed, identifying, interpreting and communicating via these IMs requires complex matching techniques. In the basic case, this matching can be done by hand, with users choosing IMs that fit with their knowledge representation or developing bridges that link the representation in the IM with their own representation. However, this puts an onerous burden on users; the system can only be usable on a large-scale if these matchings can be made automatically or interactively.